Producción CyT
Medicina - GPP SGRNA DESIGNER VS CHOP CHOP: IMPLICATIONS OF THE GENOMIC CONTEXT IN CRISPRA SGRNA DESIGN FOR ANGIOGENIC GENES
Congreso
Autoría:
Núñez Pedrozo Cristian Nahuel ; Peralta Tomás ; Belaich Mariano Nicolás ; Gimenez CS ; Crottogini AJ ; OLEA, FERNANDA DANIELA ; Cuniberti LFecha:
2020Editorial y Lugar de Edición:
MedicinaResumen *
Introduction: Angiogenic gene overexpression has been the main strategy in numerous cardiovascular regenerative gene therapy projects. However, most have failed in clinical trials, due to, among other reasons, dose inadequacy and lack of potency. CRISPRa technology enhances gene overexpression levels based on the identification of sgRNAs with maximum efficiency and safety. GPP sgRNA Designer and CHOP CHOP are the most widely used platforms for the prediction of sgRNAs, the scope of efficiency and sensitivity of their algorithms being partially uncertain. The objective of our study was to analyze the performance of GPP sgRNA Designer and CHOP CHOP for the design of sgRNAs in a panel of angiogenic genes, in a changing genetic context such as successive versions of the human genome.Materials and methods: The top 20 ranked sgRNAs were provided by GPP sgRNA Designer (GPP) and CHOP CHOP (CHOP) for each of the following VEGFA, KDR, EPO, HIF-1A, HGF, EGF, PGF, FGF1 genes from both GRCH 37 and GRCH 38 human genomes.Results: The mean ranking variation in the 20 positions was greater for GPP than CHOP in EPO (p <0.05), EGF (p <0.005), HIF-1A (p <0.005), PGF (p <0.001) and HGF (p <0.001), whereas it did not reach statistical significance in KDR, FGF-1 and VEGFA (Wilcoxon Test). Accordingly, the global accumulative change analysis for all genes was significantly greater with GPP than CHOP (14.5±8.6 vs 4.05±2.28 AUC, p <0.001, paired t-test). The rearrangement analysis of ranking positions was clearly different between platforms (GPP:-0.3187±0.2698 vs CHOP:-0.0437±0.0563, p <0.05, paired t-test).Conclusion: GPP sgRNA Designer proved to be more sensitive in establishing the best sgRNAs in relation to genomic context modifications. Second, CHOP CHOP shows a narrower classification reordering. Therefore, GPP exhibits the best performance in sgRNAs design for a panel of angiogenic genes. Información suministrada por el agente en SIGEVAPalabras Clave
GENE THERAPYANGIOGENESISCRISPRA SGRNA DESIGNER